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---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: ModernBERT-Reflections-goodareas-classifier
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/3u6o9mcs)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/ver7zql6)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/bgkconer)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/ppaajpfs)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ryanlouie2021-stanford-university/modernbert-Reflections-goodareas-sweeps/runs/0g9pz5x1)
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# ModernBERT-Reflections-goodareas-classifier
This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.2884
- Accuracy: 0.8704
- Precision: 0.3922
- Recall: 0.2105
- F1: 0.2740
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 7e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6449 | 1.0 | 461 | 0.5441 | 0.7579 | 0.2670 | 0.6211 | 0.3734 |
| 0.5152 | 2.0 | 922 | 0.4987 | 0.7604 | 0.2905 | 0.7368 | 0.4167 |
| 0.4085 | 3.0 | 1383 | 0.6748 | 0.8093 | 0.3174 | 0.5579 | 0.4046 |
| 0.2293 | 4.0 | 1844 | 2.3348 | 0.8667 | 0.3939 | 0.2737 | 0.3230 |
| 0.0264 | 5.0 | 2305 | 5.2884 | 0.8704 | 0.3922 | 0.2105 | 0.2740 |
### Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0
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